The LTAR common experiment at the Central Plains Experimental Range: Collaborative adaptive rangeland management

Authors: Augustine, David; Derner, Justin; Porensky, Lauren; Hoover, David; RITTEN, JOHN - Colorado State University; Kearney, Sean; Ma, Liwang; Peck, Dannele; Wilmer, Hailey

Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/12/2024
Publication Date: 7/22/2024
Citation: Augustine, D.J., Derner, J.D., Porensky, L.M., Hoover, D.L., Ritten, J.P., Kearney, S.P., Ma, L., Peck, D.E., Wilmer, H.N. 2024. The LTAR common experiment at the Central Plains Experimental Range: Collaborative adaptive rangeland management. Journal of Environmental Quality. Article 1-9. https://doi.org/10.1002/jeq2.20599.
DOI: https://doi.org/10.1002/jeq2.20599

Interpretive Summary: The Long-term Agroecosystem Research Network consists of 18 sites distributed across the United States where scientists are conducting long-term research on how prevailing and alternative agricultural management practices affect multiple ecosystem services. Here, we describe the primary experiment being conducted at the Central Plains Experimental Range in northeastern Colorado. This ranch-scale experiment is comparing continuous, season-long grazing management, which is a prevailing practice in the region (i.e. Traditional Rangeland Managment, TRM), with an alternative grazing management approach that was developed by a diverse stakeholder group in collaboration with USDA-ARS scientiests (Collaborative Adaptive Rangeland Mangement, CARM). For the first five years of the experiment, the CARM treatment employed adaptive, rotational grazing management where the cattle were managed as a single herd rotated through multiple pastures over the growing season based on forage availability and greeness. Each treatment was implemented on a set of 10, 130-ha pastures paired in terms of soils, topography and plant communities, to evaluate the influence of CARM on vegetation (plant composition and forage production), livestock production (steer weight gain) and wildlife habitat (vegetation structure for grassland birds). Relative to TRM, CARM enhanced heterogeneity in vegetation and habitat structure across the landscape, benefiting two grassland bird species. However, this came at the cost of lower steer weight gains in CARM vs. TRM, and declining populations of a third bird species of conservation concern in both treatments. Here we discuss how lessons learned during the experiments first five years led to changes in the CARM treatment and management objectives during the next five years. We also discuss how innovations in remote sensing, environmental sensors, ecosystem modelling, social learning, and economic analyses are being integrated into and supported by the CARM experiment.

Technical Abstract: A management-science partnership with a diverse stakeholder group is comparing collaborative adaptive rangeland management (CARM), designed to incorporate AMP principles, to traditional rangeland management (TRM) consisting of season-long grazing during the growing season. Each treatment was implemented on a set of 10, 130-ha pastures paired in terms of soils, topography and plant communities, to evaluate the influence of CARM on vegetation (plant composition and forage production), livestock production (steer weight gain) and wildlife habitat (vegetation structure for grassland birds). For the first five years of the experiment, cattle in CARM were managed as a single herd using AMP grazing with planned year-long rest in 20% of the pastures. Relative to TRM, CARM enhanced heterogeneity in vegetation and habitat structure across the landscape, benefitting two grassland bird species. However, this came at the cost of 12-16% lower steer weight gains in CARM vs. TRM, and declining populations of a third bird species of conservation concern in both treatments. Here we discuss how increased understanding of ecological and social processes during the experiments first five years led to changes in the CARM treatment and management objectives during the next five years. We also discuss how innovations in remote sensing, environmental sensors, ecosystem modelling, social learning, and economic analyses are being integrated into and supported by the CARM experiment.